Use Case
AI and Machine Learning Infrastructure on Syniel
GPU cluster training, managed experiment tracking, and production inference APIs -purpose-built for enterprise ML teams.
Key challenges
- Provisioning GPU clusters fast enough to keep ML teams unblocked
- Managing experiment reproducibility and model versioning across teams
- Serving production models with low latency and auto-scaling inference
Syniel capabilities for ai / ml training
On-Demand GPU Clusters
NVIDIA H100 NVLink clusters provision in under 5 minutes with guaranteed availability SLAs.
Managed MLflow
Enterprise MLflow with RBAC, artifact storage on Syniel Storage, and model registry with approval gates.
Inference API Gateway
Deploy models as autoscaling REST/gRPC endpoints with A/B traffic splitting and latency SLAs.
Fine-Tuning as a Service
LoRA/QLoRA fine-tuning jobs with managed compute, data preprocessing, and evaluation pipelines.
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